IVR engagements and upfront background noise

ABSTRACT

Speech recognition error may be reduced or eliminated when background noise is detected at a customer&#39;s location. For example, when background noise is detected at the customer&#39;s location, the customer may be prompted to use dual-tone multi-frequency (DTMF).

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation from U.S. patent application Ser. No.14/226,489, filed Mar. 26, 2014, entitled “IVR ENGAGEMENTS AND UPFRONTBACKGROUND NOISE”, the entire contents of which is incorporated hereinby this reference.

FIELD

The present invention relates to noise detection systems and, moreparticularly, to systems that detect background noise during a call.

BACKGROUND

Speech analysts frequently encounter upfront background noise thatcauses utterances to be grammatically incorrect. For example, if acustomer receives calls an interactive voice response (IVR) application,background noise at the customer's location may cause a delay inprocessing of the call by the IVR application. Thus, an application thatreduces or eliminates speech recognition errors due to background noisemay be beneficial.

SUMMARY

Certain embodiments of the present invention may provide solutions tothe problems and needs in the art that have not yet been fullyidentified, appreciated, or solved by current IVR applications. Forexample, embodiments of the present invention pertain to reducing oreliminating speech recognition errors when background noise at theuser's location is above a predetermined threshold.

In one embodiment, an apparatus is provided. The apparatus includesmemory including a set of instructions and at least one processor. Theset of instructions, when executed by the at least one processor, isconfigured to cause the apparatus to detect background noise at alocation of a customer and prompt the customer to use dual-tonemulti-frequency (DTMF) when the background noise at the location of thecustomer is excessive.

In another embodiment, a computer-implemented method is provided. Thecomputer-implemented method includes detecting background noise at alocation of a customer and prompting the customer to use DTMF when thebackground noise at the location of the customer is excessive.

In yet another embodiment, a computer program is provided. The computerprogram is embodied on a non-transitory computer-readable medium. Thecomputer program is configured to cause at least one processor to detectbackground noise at a location of a customer and prompt the customer touse DTMF when the background noise at the location of the customer isexcessive.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the advantages of certain embodiments of the inventionwill be readily understood, a more particular description of theinvention briefly described above will be rendered by reference tospecific embodiments that are illustrated in the appended drawings.While it should be understood that these drawings depict only typicalembodiments of the invention and are not therefore to be considered tobe limiting of its scope, the invention will be described and explainedwith additional specificity and detail through the use of theaccompanying drawings, in which:

FIG. 1 is a block diagram illustrating a computing system, according toan embodiment of the present invention.

FIG. 2 is flow diagram illustrating a conventional process for detectingan error in speech recognition.

FIG. 3 is a flow diagram illustrating a process for detecting backgroundnoise during a call, according to an embodiment of the presentinvention.

FIG. 4 is a flow diagram illustrating a process for detecting backgroundnoise during a call, according to an embodiment of the presentinvention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Embodiments of the present invention pertain to reducing or eliminatingspeech recognition errors when background noise at the customer's (orcallee) location is detected. For example, when background noise at alocation of the customer is detected, the customer may be prompted touse dual-tone multi-frequency (DTMF).

FIG. 1 illustrates a block diagram of a computing system 100, accordingto one embodiment of the present invention. Computing system 100includes a bus 105 or other communication mechanism configured tocommunicate information, and at least one processor 110, coupled to bus105, that is configured to process information. At least one processor110 can be any type of general or specific purpose processor. Computingsystem 100 also includes memory 120 configured to store information andinstructions to be executed by at least one processor 110. Memory 120can be comprised of any combination of random access memory (“RAM”),read only memory (“ROM”), static storage such as a magnetic or opticaldisk, or any other type of computer readable medium. Computing system100 also includes a communication device 115, such as a networkinterface card, configured to provide access to a network.

The computer readable medium may be any available media that can beaccessed by at least one processor 110. The computer readable medium mayinclude both volatile and nonvolatile medium, removable andnon-removable media, and communication media. The communication mediamay include computer readable instructions, data structures, programmodules, or other data and may include any information delivery media.

According to this embodiment, memory 120 stores software modules thatprovide functionality when executed by at least one processor 110. Themodules include an operating system 125 and a noise detection module130, as well as other functional modules 135. Operating system 125 mayprovide operating system functionality for computing system 100. Noisedetection module 130 may detect background noise at any time during thecall. Because computing system 100 may be part of a larger system,computing system 100 may include one or more additional functionalmodules 135 to include the additional functionality.

One skilled in the art will appreciate that a “system” could be embodiedas a personal computer, a server, a console, a personal digitalassistant (PDA), a cell phone, a tablet computing device, or any othersuitable computing device, or combination of devices. Presenting theabove-described functions as being performed by a “system” is notintended to limit the scope of the present invention in any way, but isintended to provide one example of many embodiments of the presentinvention. Indeed, methods, systems and apparatuses disclosed herein maybe implemented in localized and distributed forms consistent withcomputing technology.

It should be noted that some of the system features described in thisspecification have been presented as modules, in order to moreparticularly emphasize their implementation independence. For example, amodule may be implemented as a hardware circuit comprising custom verylarge scale integration (VLSI) circuits or gate arrays, off-the-shelfsemiconductors such as logic chips, transistors, or other discretecomponents. A module may also be implemented in programmable hardwaredevices such as field programmable gate arrays, programmable arraylogic, programmable logic devices, graphics processing units, or thelike.

A module may also be at least partially implemented in software forexecution by various types of processors. An identified unit ofexecutable code may, for instance, comprise one or more physical orlogical blocks of computer instructions that may, for instance, beorganized as an object, procedure, or function. Nevertheless, theexecutables of an identified module need not be physically locatedtogether, but may comprise disparate instructions stored in differentlocations which, when joined logically together, comprise the module andachieve the stated purpose for the module. Further, modules may bestored on a computer-readable medium, which may be, for instance, a harddisk drive, flash device, random access memory (RAM), tape, or any othersuch medium used to store data.

Indeed, a module of executable code could be a single instruction, ormany instructions, and may even be distributed over several differentcode segments, among different programs, and across several memorydevices. Similarly, operational data may be identified and illustratedherein within modules, and may be embodied in any suitable form andorganized within any suitable type of data structure. The operationaldata may be collected as a single data set, or may be distributed overdifferent locations including over different storage devices, and mayexist, at least partially, merely as electronic signals on a system ornetwork.

FIG. 2 is flow diagram 200 illustrating a conventional process fordetecting an error in speech recognition. The conventional processbegins at 205 with an IVR system placing a call to a customer. The callcan be placed for any reason. For example, when a customer dials intothe IVR system, agents may be busy and the customer may request that theIVR system place a call to the customer when an agent is available. Inanother example, the IVR system may call a customer when the customer isinadvertently disconnected from the IVR system.

At 210, the IVR system plays an introduction message to the customer,and, at 215, prompts the customer using speech recognition. At 220, ifthe IVR system detects an error during speech recognition, the IVRsystem prompts the customer to use DTMF at 225. If the IVR system doesnot detect an error during speech recognition at 220, then the IVRsystem continues with the voice recognition process at 230 to connectthe customer to an appropriate agent.

The process illustrated in FIG. 2 may encounter a number of problems.For example, depending on the configuration of the IVR, numerous amountsof retries may be provided to the customer when the system cannotrecognize the utterance due to background noise at the customer'slocation. To overcome such problems, the process shown in FIG. 3 may beutilized.

FIG. 3 is a flow diagram 300 illustrating a process for detectingbackground noise during a call, according to an embodiment of thepresent invention. The process of FIG. 3 may be executed by, forexample, by computing system 100 of FIG. 1. In this embodiment, thecomputing system at 305 calls a customer and, at 310, plays anintroduction message when the customer answers the call. In certainembodiments, the welcome message is played to the customer immediatelyafter, or after a brief delay, the customer answers a call from the IVRsystem.

At 315, the computing system determines whether the background noise atthe customer's location is above a noise floor (or background noiselevel). A speech recognizer may be utilized to determine noise, and setassociate ‘acceptable levels” of noise. In certain embodiments, thenoise floor may be determined while the introduction message is played.In other embodiments, the noise floor may be determined after completionof the welcome message. If the noise level is above the noise floor, thecomputing system at 340 prompts the customer to use DTMF to complete thecall flow to connect to an agent, for example. When the noise level isat or below the noise floor, the process continues with the IVRapplication.

Because background noise may fluctuate (i.e., increase or decrease) atthe location of the customer from one sampling period to the next, thecomputing system at 320 continues to listen to the background noise atthe location of the customer, and, at 325, determines whether thebackground noise is excessive. For example, the computing system maydetect whether the location of the customer contains a sufficient degreeof background noise such that successful speech recognition isimpossible. This may be measured, for example, by a signal strength ofthe background noise, a number of decibels of the background noise, orany other noise analysis technique that would be understood by one ofordinary skill in the art. It should also be appreciated that the levelof background noise may be determine during each prompt, or after theIVR application has prompted the user to provide a response.

If the computing system detects excessive background noise, then at 340the customer is prompted to use DTMF to complete the call flow toconnect to an agent, for example. If the computing system does notdetect excessive background noise at 325, then at 330, the customer isprompted using speech recognition.

At 335, the computing system detects whether a speech recognition errorhas occurred. If a speech recognition error has occurred, then at 340,the customer is prompted to use DTMF to complete the call flow toconnect to the agent, for example. Otherwise, the call flow continues at345 to connect the user to the agent.

It should be appreciated that in certain embodiments, the backgroundnoise detection is activated throughout the call to ensure that thecustomer is connected to the agent promptly. The embodiments discussedherein may reduce customer frustration and shorten the call length.Furthermore, by detecting noisy environments, a greater insight isprovided into how well speech recognition works in an ideal environmentand how often the customer is not in an ideal calling environment (e.g.,outside in traffic, music playing, conversation in background, etc.).

FIG. 4 is a flow diagram 400 illustrating a process for detectingbackground noise during a call, according to an embodiment of thepresent invention. The process of FIG. 4 may be executed by, forexample, computing system 100 of FIG. 1.

In this embodiment, the computing system at 405 places a call to thecustomer, who answers the phone, and at 410, the computing system startsto listen to background noise at a location of the customer prior toplaying the welcome message.

At 415, the computing system plays a welcome message to the customer. Incertain embodiments, the welcome message is played to the customer whenthe customer picks up the phone. At 420, the computing system stopslistening to the background noise at the location of the customer, and,at 425, determines whether the background noise is excessive. Forexample, the computing system may detect whether the location of thecustomer contains a sufficient degree of background noise such thatsuccessful speech recognition is impossible. This may be measured, forexample, by a signal strength of the background noise, a number ofdecibels of the background noise, or any other noise analysis techniquethat would be understood by one of ordinary skill in the art.

In other embodiments, the computing system may compare the noise floorwith the background noise. For example, if the background noise isgreater than the noise floor, then the background noise is considered tobe excessive. Otherwise, the background noise is considered to benon-excessive.

If the computing system detects excessive background noise, then at 440,the customer is prompted to use DTMF to complete the call flow toconnect to an agent, for example. If the computing system does notdetect excessive background noise at 425, then at 430, the customer isprompted using the speech recognition.

At 435, the computing system detects whether speech recognition errorhas occurred. If speech recognition error has occurred, then at 440, thecustomer is prompted to use DTMF to complete the call flow to connect,for example, to the agent. Otherwise, the call flow continues at 445 toconnect the customer to the agent, for example.

It should be appreciated that in certain embodiments, the backgroundnoise detection is activated throughout the call to ensure that thecustomer is connected to the agent promptly. The embodiments discussedherein may reduce customer frustration and shorten the call length.Furthermore, by detecting noisy environments, a greater insight isprovided into how well speech recognition works in an ideal environmentand how often customers are not in an ideal environment.

The processes shown in FIGS. 3 and 4 may be performed, in part, by acomputer program, encoding instructions for a nonlinear adaptiveprocessor to cause at least the processes described in FIGS. 3 and 4 tobe performed by the apparatuses discussed herein. The computer programmay be embodied on a non-transitory computer readable medium. Thecomputer readable medium may be, but is not limited to, a hard diskdrive, a flash device, a random access memory, a tape, or any other suchmedium used to store data. The computer program may include encodedinstructions for controlling the nonlinear adaptive processor toimplement the processes described in FIGS. 3 and 4, which may also bestored on the computer readable medium.

The computer program can be implemented in hardware, software, or ahybrid implementation. The computer program can be composed of modulesthat are in operative communication with one another, and which aredesigned to pass information or instructions to display. The computerprogram can be configured to operate on a general purpose computer, oran application specific integrated circuit (“ASIC”).

It will be readily understood that the components of the invention, asgenerally described and illustrated in the figures herein, may bearranged and designed in a wide variety of different configurations.Thus, the detailed description of the embodiments is not intended tolimit the scope of the invention as claimed, but is merelyrepresentative of selected embodiments of the invention.

The features, structures, or characteristics of the invention describedthroughout this specification may be combined in any suitable manner inone or more embodiments. For example, the usage of “certainembodiments,” “some embodiments,” or other similar language, throughoutthis specification refers to the fact that a particular feature,structure, or characteristic described in connection with an embodimentmay be included in at least one embodiment of the invention. Thus,appearances of the phrases “in certain embodiments,” “in someembodiments,” “in other embodiments,” or other similar language,throughout this specification do not necessarily all refer to the sameembodiment or group of embodiments, and the described features,structures, or characteristics may be combined in any suitable manner inone or more embodiments.

One having ordinary skill in the art will readily understand that theinvention as discussed above may be practiced with steps in a differentorder, and/or with hardware elements in configurations that aredifferent than those which are disclosed. Therefore, although theinvention has been described based upon these preferred embodiments, itwould be apparent to those of skill in the art that certainmodifications, variations, and alternative constructions would beapparent, while remaining within the spirit and scope of the invention.In order to determine the metes and bounds of the invention, therefore,reference should be made to the appended claims.

What is claimed is:
 1. An apparatus, comprising: memory comprising a setof instructions; and at least one processor, wherein the set ofinstructions, when executed by the at least one processor, areconfigured to cause the apparatus to: determine a noise floor after acall is answered by a customer based on a signal strength of backgroundnoise; set an acceptable level of background noise to use with aninteractive voice response (IVR) application during the call; and promptthe customer to use dual-tone multi-frequency (DTMF) when the backgroundnoise is above the noise floor after the IVR application has provided aprompt to the customer.
 2. The apparatus of claim 1, wherein the set ofinstructions, when executed by the at least one processor, are furtherconfigured to cause the apparatus to listen for the background noise atthe location of the customer when a call is answered by the customer. 3.The apparatus of claim 1, wherein the set of instructions, when executedby the at least one processor, are further configured to cause theapparatus to detect the signal strength of the background noise at thelocation of the customer during the call.
 4. The apparatus of claim 1,wherein the set of instructions, when executed by the at least oneprocessor, are further configured to cause the apparatus to determinethe background noise at the location of the customer is above the noisefloor after the IVR application has provided the prompt to the customer.5. The apparatus of claim 1, wherein the set of instructions, whenexecuted by the at least one processor, are further configured to causethe apparatus to determine whether speech recognition error occurredduring the call.
 6. The apparatus of claim 1, wherein the set ofinstructions, when executed by the at least one processor, are furtherconfigured to cause the apparatus to instruct the customer to use DTMFwhen speech recognition error is detected during the call.
 7. Theapparatus of claim 1, wherein the set of instructions, when executed bythe at least one processor, are further configured to cause theapparatus to detect the noise floor at a location of the customer whilean introduction message to the customer is played.
 8. Acomputer-implemented method, comprising: determining a noise floor aftera call is answered by a customer based on a signal strength ofbackground noise; setting an acceptable level of background noise to usewith an interactive voice response (IVR) application during the call;and prompting the customer to use dual-tone multi-frequency (DTMF) whenthe background noise is above the noise floor after the IVR applicationhas provided a prompt to the customer.
 9. The computer-implementedmethod of claim 8, further comprising listening, by the computingsystem, for the background noise at the location of the customer after acall is answered by the customer.
 10. The computer-implemented method ofclaim 8, further comprising detecting the signal strength of thebackground noise at the location of the customer during the call. 11.The computer-implemented method of claim 8, further comprisingdetermining, by the computing system, whether the background noise atthe location of the customer is excessive.
 12. The computer-implementedmethod of claim 8, further comprising determining the background noiseat the location of the customer is above the noise floor after the IVRapplication has provided the prompt to the customer.
 13. Thecomputer-implemented method of claim 8, further comprising determining,by the computing system, whether speech recognition error occurredduring the call.
 14. The computer-implemented method of claim 8, furthercomprising detecting, by the computing system, the noise floor at alocation of the customer while playing an introduction message to thecustomer.
 15. A computer program embodied on a non-transitorycomputer-readable medium, the computer program configured to cause atleast one processor to: determine a noise floor after a call is answeredby a customer based on a signal strength of background noise, set anacceptable level of background noise to use with an interactive voiceresponse (IVR) application during the call; and prompt the customer touse dual-tone multi-frequency (DTMF) when the background noise is abovethe noise floor after the IVR application has provided a prompt to thecustomer.
 16. The computer program of claim 15 wherein the computerprogram is further configured to cause the at least one processor tolisten for background noise at the location of the customer after a callis answered by the customer.
 17. The computer program of claim 15wherein the computer program is further configured to cause the at leastone processor to detect the signal strength of the background noise atthe location of the customer during the call.
 18. The computer programof claim 15, wherein the computer program is further configured to causethe at least one processor to determine whether speech recognition erroroccurred during the call.
 19. The computer program of claim 15, whereinthe computer program is further configured to cause the at least oneprocessor to instruct the customer to use DTMF when speech recognitionerror is detected during the call.
 20. The computer program of claim 15,wherein the computer program is further configured to cause the at leastone processor to detect the noise floor at the location of the customerwhile to playing an introduction message to the customer.